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Record W2324911097 · doi:10.1177/0095798414568454

Ethnic and Racial Self-Identifications of Second-Generation Canadians of African and Caribbean Heritage

2015· article· en· W2324911097 on OpenAlexaffabout
Rashelle Litchmore, Saba Safdar, Kieran C. O’Doherty

Bibliographic record

VenueJournal of Black Psychology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEthnic groupNationalityGender studiesPsychologyPerformative utteranceSocial psychologySociologyAnthropologyImmigrationGeographyLinguistics

Abstract

fetched live from OpenAlex

This study investigated how second-generation Canadian youth of African and Caribbean heritage constructed racial, ethnic, and national identities and categories. Twenty-two participants aged 13 to 18 years of East and West African, and Caribbean background, were recruited from communities in the Greater Toronto Area to participate in four discussion groups. Discourse analysis was used to demonstrate the fluidity and negotiability of racial and ethnic identities and categories. Participants constructed the category of “Black” using historical, social, and descriptive references and in support of their identifications or lack thereof with this category. Categories associated with “ethnicity” and nationality were also constructed to support participants’ identifications, with some contradictory representations. Disagreements over category constructions were also present. The study highlights the performative, as opposed to cognitive, features of identities. It also brings attention to how flexible the characterizations of racial and ethnic labels can be and argues for researcher consideration of this flexibility in relation to their participants and to the social contexts of their research. Implications for research in Canadian contexts are also discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.116
GPT teacher head0.415
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations60
Published2015
Admission routes2
Has abstractyes

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